{"id":1131,"date":"2009-12-24T16:55:26","date_gmt":"2009-12-24T22:55:26","guid":{"rendered":"http:\/\/hunch.net\/?p=1131"},"modified":"2009-12-24T16:55:26","modified_gmt":"2009-12-24T22:55:26","slug":"top-graduates-this-season","status":"publish","type":"post","link":"https:\/\/hunch.net\/?p=1131","title":{"rendered":"Top graduates this season"},"content":{"rendered":"

I would like to point out 3 graduates this season as having my confidence they are capable of doing great things. <\/p>\n

    \n
  1. Daniel Hsu<\/a> has diverse papers with diverse coauthors on {active learning, mulitlabeling, temporal learning, …} each covering new algorithms and methods of analysis. He is also a capable programmer, having helped me with some nitty-gritty details of cluster parallel Vowpal Wabbit<\/a> this summer. He has an excellent tendency to just get things done.<\/li>\n
  2. Nicolas Lambert<\/a> doesn’t nominally work in machine learning, but I’ve found his work in elicitation<\/a> relevant nevertheless. In essence, elicitable properties are closely related to learnable properties, and the elicitation complexity is related to a notion of learning complexity. See the Surrogate regret bounds paper<\/a> for some related discussion. Few people successfully work at such a general level that it crosses fields, but he’s one of them.<\/li>\n
  3. Yisong Yue<\/a> is deeply focused on interactive learning, which he has attacked at all levels: theory, algorithm adaptation, programming, and popular description<\/a>. I’ve seen a relentless multidimensional focus on a new real-world problem be an excellent strategy for research and expect he’ll succeed.<\/li>\n<\/ol>\n

    The obvious caveat applies—I don’t know or haven’t fully appreciated everyone’s work so I’m sure I missed people. I’d like to particularly point out Percy Liang<\/a> and David Sontag<\/a> as plausibly such whom I’m sure others appreciate a great deal.<\/p>\n","protected":false},"excerpt":{"rendered":"

    I would like to point out 3 graduates this season as having my confidence they are capable of doing great things. Daniel Hsu has diverse papers with diverse coauthors on {active learning, mulitlabeling, temporal learning, …} each covering new algorithms and methods of analysis. He is also a capable programmer, having helped me with some … <\/p>\n

    Continue reading “Top graduates this season”<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[63,29],"tags":[],"class_list":["post-1131","post","type-post","status-publish","format-standard","hentry","category-graduates","category-machine-learning"],"_links":{"self":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts\/1131","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1131"}],"version-history":[{"count":0,"href":"https:\/\/hunch.net\/index.php?rest_route=\/wp\/v2\/posts\/1131\/revisions"}],"wp:attachment":[{"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1131"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1131"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hunch.net\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1131"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}